Smart lighting systems offer the opportunity to significantly increase the utility of a lighting infrastructure. Such systems may, for example, decrease energy consumption by dynamically lowering the output of lights when light is not needed in at certain luminosity levels or at all. It is difficult, however, to appropriately adjust light levels to maximize energy savings without negatively impacting the human experience of the light. This difficulty is exacerbated by the limitations of sensors, as all sensors typically have limited range, accuracy, and reliability. Without significant tools, manual light level optimizations may be laborious and time-intensive.